Electromyography (EMG)

14 papers with code • 0 benchmarks • 1 datasets

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Most implemented papers

Parkinson’s Disease EMG Data Augmentation and Simulation with DCGANs and Style Transfer

larocs/EMG-GAN 3 May 2020

This paper proposes two new data augmentation approaches based on Deep Convolutional Generative Adversarial Networks (DCGANs) and Style Transfer for augmenting Parkinson’s Disease (PD) electromyography (EMG) signals.

sEMG Gesture Recognition with a Simple Model of Attention

josephsdavid/semg_repro 5 Jun 2020

Myoelectric control is one of the leading areas of research in the field of robotic prosthetics.

Boosting Factor-Specific Functional Historical Models for the Detection of Synchronisation in Bioelectrical Signals

davidruegamer/BoostingSignalSynchro 20 Sep 2016

The link between different psychophysiological measures during emotion episodes is not well understood.

EV-Action: Electromyography-Vision Multi-Modal Action Dataset

wanglichenxj/EV-Action-Electromyography-Vision-Multi-Modal-Action-Dataset 20 Apr 2019

To make up this, we introduce a new, large-scale EV-Action dataset in this work, which consists of RGB, depth, electromyography (EMG), and two skeleton modalities.

Parkinson’s Disease EMG Signal Prediction Using Neural Networks

larocs/EMG-prediction 6 Oct 2019

This paper proposes a comparison between different neural network models, using multilayer perceptron (MLPs) and recurrent neural network (RNN) models, for predicting Parkinson's disease electromyography (EMG) signals, to anticipate resulting resting tremor patterns.

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

coreylammie/TBCAS-Towards-Healthcare-and-Biomedical-Applications 11 Jul 2020

The advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors has brought on new opportunities for applying both Deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge.

Digital Voicing of Silent Speech

dgaddy/silent_speech EMNLP 2020

In this paper, we consider the task of digitally voicing silent speech, where silently mouthed words are converted to audible speech based on electromyography (EMG) sensor measurements that capture muscle impulses.

End-to-end grasping policies for human-in-the-loop robots via deep reinforcement learning

sharif1093/dextron 26 Apr 2021

State-of-the-art human-in-the-loop robot grasping is hugely suffered by Electromyography (EMG) inference robustness issues.

An Improved Model for Voicing Silent Speech

dgaddy/silent_speech ACL 2021

In this paper, we present an improved model for voicing silent speech, where audio is synthesized from facial electromyography (EMG) signals.

Towards Predicting Fine Finger Motions from Ultrasound Images via Kinematic Representation

deanzadok/finemotions 10 Feb 2022

A central challenge in building robotic prostheses is the creation of a sensor-based system able to read physiological signals from the lower limb and instruct a robotic hand to perform various tasks.